Book Image

Hadoop 2.x Administration Cookbook

By : Aman Singh
Book Image

Hadoop 2.x Administration Cookbook

By: Aman Singh

Overview of this book

Hadoop enables the distributed storage and processing of large datasets across clusters of computers. Learning how to administer Hadoop is crucial to exploit its unique features. With this book, you will be able to overcome common problems encountered in Hadoop administration. The book begins with laying the foundation by showing you the steps needed to set up a Hadoop cluster and its various nodes. You will get a better understanding of how to maintain Hadoop cluster, especially on the HDFS layer and using YARN and MapReduce. Further on, you will explore durability and high availability of a Hadoop cluster. You’ll get a better understanding of the schedulers in Hadoop and how to configure and use them for your tasks. You will also get hands-on experience with the backup and recovery options and the performance tuning aspects of Hadoop. Finally, you will get a better understanding of troubleshooting, diagnostics, and best practices in Hadoop administration. By the end of this book, you will have a proper understanding of working with Hadoop clusters and will also be able to secure, encrypt it, and configure auditing for your Hadoop clusters.
Table of Contents (20 chapters)
Hadoop 2.x Administration Cookbook
Credits
About the Author
About the Reviewers
www.PacktPub.com
Customer Feedback
Preface
Index

Benchmarking Hadoop cluster


It is important to benchmark so as to have a baseline to do comparisons after making changes. In this recipe, we will look at some of the benchmarks which can help to profile the changes committed.

Before running any tests for the changed parameters, make sure to enable verbose logging and also enable GC logs for all the components by using -verbose:gc -XX:+PrintGCDetails -XX:+PrintGCTimeStamps -XX:+PrintGCDateStamps -Xloggc:${LOG_DIR}/gc-{component}.log-$(date +'%Y%m%d%H%M').

Getting ready

Make sure that the user has a running cluster with HDFS and YARN fully functional in a multi-node cluster.

All these tests must be run first without making any changes to the cluster and then optimizing parameters, discussed in the preceding recipes, and again running the benchmarking test.

How to do it...

Connect to the Edge node client1.cyrus.com or master node and change to the Hadoop user.

All test output will be written to the location /bencharks on HDFS, under respective test...